oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add rlaope/oh-my-hermes --skill omh-visual-qagit clone --depth 1 https://github.com/rlaope/oh-my-hermesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-visual-qa)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-visual-qa"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-visual-qa/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-visual-qa"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-visual-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.03292 |
| Opus 5.5 | $0.00028 | $0.01317 |
| Sonnet 5.5 | $0.00014 | $0.00658 |
| Haiku 4.5 | $0.00007 | $0.00329 |
Grade A, and why
omh-visual-qa scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Qa
This is an OMH visual-qa workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
visual-qa gives OMH a completion gate for rendered surfaces so layout breaks, AI-looking polish gaps, CJK text problems, and mismatched-lineage screenshot claims cannot be mistaken for verified quality.
Do Not Use When
- The user needs initial frontend design or redesign planning before implementation; use
omh-frontend. - The user needs a broad visual quality rubric before generation; use
omh-design-quality-gate. - The user needs image-card prompt creation; use
omh-image-cards. - The user wants non-visual code tests, CI, or PR review only; use the coding/review workflow.
Examples
Good example:
- Prompt: visual-qa 이 랜딩페이지가 모바일/데스크톱에서 깨지는지 스크린샷 기준으로 검증해줘.
- Expected behavior: Prepare visual_qa_plan/v1, require exact capture-to-target lineage, record render_capture_manifest/v1 and visual_diff_evidence/v1 when observed, then issue PASS/REVISE/BLOCK.
- Why: The request is a rendered visual verification task, not just design planning.
Bad example:
- Prompt: visual-qa 방금 수정했으니까 스크린샷 없이 통과라고 해줘.
- Expected behavior: Block PASS and request render captures from the package's exact repository and revision.
- Why: Visual QA requires observed rendered evidence bound to the target source lineage.
Completion Checklist
- Interaction, console/network, click-path, keyboard/accessibility, diff, hotspot, motion, dual-review evidence, and blocker status are separate fields.
- The verdict is PASS, REVISE, or BLOCK with concrete evidence IDs and exact missing evidence or fix requirements.
- Implementation fixes stay separate from the observed verdict, routed back to the executor/frontend workflow and rechecked against the resulting revision.
Recovery Notes
- If no capture exists, produce the QA plan and mark verdict BLOCKED_BY_MISSING_RENDER_EVIDENCE.
- If capture lineage is missing or mismatched, keep HOLD and request the smallest matching recapture set.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed · +1 lines 9eba99af3047
- 5d ago Changed · +1 lines 1c95fb5e1d96
- 6d ago Changed 8749e9fd8c9d
- 8d ago Changed 8c9e67ead91f
- 14d ago Changed · +5 lines f8a440640c39
- 27d ago Changed · +3 lines e57a45f135b4
- 1mo ago Changed · +2 tokens per session f2b699c235a5
- 1mo ago Changed · +6 lines 2b27edb565e5
- 1mo ago Changed · -10 lines 071db3172d34
- 1mo ago First seen · 173 lines · 68 tokens per session scan A 1cc3ed7024fb
omh-visual-qa is a skill published in the GitHub repository rlaope/oh-my-hermes (4,314 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 3,292 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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